EP4073473B1 - Method for optimizing a measurement rate of a field device - Google Patents

Description

The invention relates to a method for optimizing a measuring rate of a field device in a measuring system.

In automation technology, particularly for process automation, field devices are often used to record various measured variables. The measured variable to be determined can be, for example, a fill level, a flow rate, a pressure, the temperature, the pH value, the redox potential, a conductivity or the dielectric value of a medium in a process plant. To record the corresponding measured values, the field devices each contain suitable sensors or are based on suitable measuring principles. A large number of different types of field devices are manufactured and sold by the Endress + Hauser group of companies.

In the respective process plant, the individual field devices are usually connected to form a measuring system in order to be able to coordinate the corresponding process variables with suitable actuators, such as heating elements, agitators, valves or pumps for inflow and outflow. Accordingly, the measured variables of the individual field devices of a process plant may also correlate with one another. For communication within the measuring system, the field devices can be connected to one another either directly or centrally via a control unit, such as a process control center. Especially for field devices that are located in hard-to-reach places in the process plant, wireless transmission protocols such as wireless HART or WLAN are preferably implemented for communication within the measuring system. In these cases, these field devices are powered by batteries. The potential service life of the individual field device depends on the capacity of the battery and the measuring rate, i.e. the clocking and measuring time per clock with which the field device measures the measured value.

In this context, however, the measurement rate must not be set too low so that the process can be adequately monitored. In In connection with the finite capacity of the battery, the corresponding field devices must therefore be taken out of operation during regular maintenance cycles in order to change the battery. As a result, the processes within the process plant must also be stopped during these maintenance periods, as the processes cannot usually run in a controlled manner without appropriate monitoring. This is disadvantageous for the plant operator, as any downtime of the process plant affects its profitability.

TAYEH GABY BOU ET AL: "A Spatial-Temporal Correlation Approach for Data Reduction in Cluster-Based Sensor Networks " discloses a method for data reduction using spatial and temporal correlation of sensor measurement data.

The invention is therefore based on the object of providing a method with which the availability of battery-operated field devices can be increased.

• Messung der Messgrößen der zumindest zwei Feldgeräte mit jeweils einer voreingestellten Mess-Rate während einer definierten Einlernphase,
• Bestimmung eines Korrelations-Musters zwischen der ersten Messgröße und der zweiten Messgröße anhand der in der Einlernphase gemessenen Messwerte.

The invention solves this problem by a method for optimizing a measurement rate of a first field device in a measuring system. To use the method, it is necessary that the measuring system comprises at least one second field device in addition to the first field device, wherein the at least two field devices each measure measured values of corresponding measured variables at a specific measurement rate, and wherein at least the measured variable of the first field device correlates with the measured variable of the second field device. The method comprises the following method steps:

• Measurement of the measured variables of at least two field devices with a preset measuring rate during a defined learning phase,
• Determination of a correlation pattern between the first measured variable and the second measured variable based on the measured values measured in the learning phase.

At least the measured values of the second field device are checked for the correlation pattern during a measurement operation,
wherein the measuring rate of the first field device in the measuring operation is changed at least during the time window in which the correlation pattern is detected in the measured values of the second measured quantity.

The optimal correlation pattern, such as a Pearson or partial correlation, can be determined using an auto machine learning algorithm.

The invention is therefore based on checking the correlation of the individual measured variables with each other. If the method detects a strong correlation between the measured variables, this is considered proof that the measuring system is functioning properly. In the other case, it is assumed that there is a malfunction in the measuring system, so that the measured values are to be classified as incorrect or at least not trustworthy.

The measuring rate of the first field device can be reduced during measuring operation, at least during the time window in which the correlation pattern is detected in the measured values of the second measured variable. This can reduce the power consumption of the respective device. This is particularly advantageous if the first field device and/or the second field device include a battery for power supply, as this increases the battery life and thus the availability in the process plant.

In order to reduce any computational effort and thus accelerate the creation of the correlation pattern, redundant measured values from the learning phase can advantageously be filtered out to determine the correlation pattern, for example by means of an unsupervised clustering procedure.

• Eine erstes Feldgerät, das ausgelegt ist, die erste Messgröße mit einer einstellbaren Mess-Rate zu messen,
• eine zweites Feldgerät, das ausgelegt ist, die zweite Messgröße zu messen,
• eine Steuer-Einheit, die ausgelegt ist, um
  • ∘ ein Korrelations-Muster zwischen der ersten Messgröße und der zweiten Messgröße anhand der in der Einlernphase gemessenen Messwerte zu bestimmen,
  • ∘ zumindest die Messwerte des zweiten Feldgerätes während des Messbetriebs auf das Korrelations-Muster hin zu prüfen,
  • o zumindest die Mess-Rate des ersten Feldgerätes im Messbetrieb zumindest während eines Zeitfensters, in dem das Korrelations-Muster bei den Messwerten der zweiten Messgröße erkannt wird, zu ändern.

A corresponding measuring system suitable for carrying out the method according to one of the preceding embodiments must comprise at least the following components:

• A first field device configured to measure the first measured variable at an adjustable measuring rate,
• a second field device designed to measure the second measured quantity,
• a control unit designed to
  • ∘ to determine a correlation pattern between the first measured variable and the second measured variable based on the measured values measured in the learning phase,
  • ∘ to check at least the measured values of the second field device for the correlation pattern during the measurement operation,
  • o to change at least the measuring rate of the first field device in measuring operation at least during a time window in which the correlation pattern is detected in the measured values of the second measured quantity.

The first field device and/or the second field device can be connected to the control unit, for example, via a wireless interface.

In the context of the invention, the term " unit " is understood to mean in principle any electronic circuit that is suitably designed for the intended purpose. Depending on the requirements, it can therefore be an analog circuit for generating or processing corresponding analog signals. However, it can also be a digital circuit such as an FPGA or a storage medium in conjunction with a program. The program is designed to carry out the corresponding process steps or to apply the necessary computing operations of the respective unit. In this context, different electronic units of the level measuring device within the meaning of the invention can potentially also access a common physical memory or be operated using the same physical digital circuit.

• Fig. 1: Ein Mess-System mit drei Feldgeräten in einer Prozessanlage, und
• Fig. 2: eine Korrelation zwischen den Messgrößen der Feldgeräte.

The invention is explained in more detail using the following figures. It shows:

• Fig.1 : A measuring system with three field devices in a process plant, and
• Fig.2 : a correlation between the measured values of the field devices.

For a general understanding of the method according to the invention, Fig.1 an exemplary measuring system 1 is shown, which serves to monitor a process plant 2, such as a chemical reactor. For this purpose, the exemplary measuring system 1 comprises as field devices a flow meter 12 at an inlet of the reactor 2, a level meter 11 on the reactor 2 itself, and a temperature measuring device 13 at an outlet of the reactor 2. The field devices 11, 12, 13 measure the corresponding measured values L, f, T each with an individually adjustable measuring rate, for example between 1 measurement per minute and 1000 measurements per second.

For example, reaction reactants can be fed in via the inlet of the reactor 2, wherein the flow rate f at which the reaction reactant is fed in is recorded by means of the flow meter 12.

Schematisch dargestellt ist diese Korrelation der Füllstands-Messwerte mit denen des Durchflussmessgerätes 12 in dem Graph von Fig. 2 The level measuring device 11 measures the level L in the reactor 2 and thus monitors, for example, whether a critical level value L is exceeded or not reached due to the reaction or due to the supply of the reaction educt. Accordingly, the measured values of the level measuring device 11 in the exemplary process plant 2 correlate with the measured values of the flow measuring device 12 in that the level L in the reactor 2 increases linearly over time in the time interval Δt in which a constant flow rate f prevails in the inlet. This exemplary correlation of the level L in relation to the flow f can thus be described functionally, since the level is formed by the primitive function of the flow: $$L\left(t\right)=\mathit{const}.+\stackrel{\mathrm{\Delta }t}{{\displaystyle \int e}}\left(t\right)\mathit{engl}$$

This correlation of the level measurements with those of the flow meter 12 is shown schematically in the graph of Fig.2

The temperature measuring device 13 at the outlet of the reactor 2 can be Fig.1 shown embodiment can in turn be used to measure the temperature T of a reaction product when emptying the reactor 2, for example in order to adapt subsequent process steps accordingly. If any chemical reactions in the process plant 2 are endothermic and therefore lead to cooling in the reactor 2, the temperature measuring device 13 registers at least a short drop in the temperature T during the corresponding time interval Δt ₂ in which the reactor 2 is emptied, depending on the ambient temperature. Accordingly, the Measured values of the temperature measuring device 13 with a (time-linear) decrease in the filling level L with the measured values of the filling level measuring device 11. This exemplary relationship is also shown schematically in the graph of Fig.2 shown.

At the Fig.1 In the embodiment shown, the measuring system 1 comprises a control unit 14 to which the field devices 11, 12, 13 are connected. The control unit 14 can be, for example, the process control system of the process plant. The interface via which the field devices 11, 12, 13 are connected to the control unit 14 can be implemented as "PROFIBUS", "HART", "Wireless HART" or "Ethernet". Especially with a wireless design of the interfaces, the field devices 11, 12, 13 can be operated using a battery, so that no additional cabling is required.

The measured values f, L, T measured by the field devices 11, 12, 13 can be transmitted via the interfaces. With appropriate design, the control unit 4 is thereby able to determine the previously described correlation patterns between the level measured values and the measured values f of the flow meter 12 or the temperature measured values and the level measured values during a defined learning phase. To find a suitable correlation type, such as a Pearson or partial correlation, the control unit 14 can, for example, use an auto-machine learning algorithm.

After detecting the correlation pattern, the measuring system 1 according to the invention or the control unit 14 can switch to regular measuring operation. This means that during the measuring operation, the control unit 14 checks at least the measured values f of the flow meter 12 for the previously determined correlation pattern. Specifically, it is checked whether a (constant) flow rate f currently prevails. If this is detected, it is deduced from this that the fill level L must also change accordingly due to the previously detected correlation pattern.

Since the change in the filling level is predictable due to this type of correlation, the measuring rate of the filling level measuring device 11 in the measuring mode can be reduced at least during the time window Δt in which the correlation pattern is recognized in the flow measurement values f, without an unpredictable abrupt change in the filling level L being expected. In this way, in the event that the filling level measuring device 11 is battery-operated, its service life and thus its availability can be optimized.

Analogous to the flow measurement values f of the flow meter 12, the control unit 14 can also check the measurement values L of the level measuring device 11 for the previously defined correlation pattern of the temperature measuring device 13 with regard to the level measurement values L during measuring operation. As soon as a decrease in the level is detected, this is again recognized as the presence of the correlation pattern and a corresponding (short-term) reduction in the temperature T on the temperature measuring device 13 is anticipated. Consequently, the measurement rate of the temperature measuring device 13 in measuring operation can also be reduced at least during the time window Δt ₂ in which the correlation pattern is recognized in the level values L, without an unforeseen change in temperature being expected. This also means that the service life or the availability of the temperature measuring device 13 can be increased in the case of battery operation.

The control unit 14 is shown as a separate, higher-level unit in the illustration shown. Within the scope of the invention, however, it is also conceivable to design the control unit 4 not as an external device, but as a component of one of the field devices 11, 12, 13.

List of reference symbols

1

Measuring system

2

Process plant

11

Level measuring device

12

Flow meter

13

Temperature measuring device

14

Control unit

e

Flow rate

L

Fill level

T

temperature

Δt

Time window

Claims (7)

1. A method for optimizing a measurement rate of a first field device (11) in a measuring system (1), wherein the first field device (11) is configured to measure a first measured variable (L) with an adjustable measurement rate, wherein the measuring system (1), in addition to the first field device (11), comprises at least a second field device (12), which is configured to measure a second measured variable (f), wherein the first measured variable (L) is different from the second measured variable (f), and wherein at least the first measured variable (L) of the first field device (11) correlates with the second measured variable (f) of the second field device (12), comprising the following process steps:

   - Measuring the measured variables (f, L) of the at least two field devices (11, 12) each with a preset measurement rate during a defined calibration phrase,

   - working out a correlation pattern between the first measured variable (L) and the second measured variable (f) based on the measured values from the calibration phase,

   - implementing measuring mode,

   wherein at least the measured values of the second field device (12) are checked in relation to the correlation pattern during measuring mode, and

   wherein the measurement rate of the first field device (11) in measuring mode is changed at least during a time window (Δt) in which the correlation pattern is detected in the measured values of the second measured variable (f).
2. The method as claimed in claim 1, wherein the correlation pattern is worked out using an automated machine learning algorithm.
3. The method as claimed in one of the preceding claims, wherein the measurement rate of the first field device (11) in measuring mode is reduced at least during the time window (Δt) in which the correlation pattern is detected in the measured values of the second measured variable (f).
4. The method as claimed in claims 1 to 3, wherein redundant measured values from the calibration phase are filtered out, in particular using an unsupervised clustering method, in order to work out the correlation pattern.
5. A measuring system for implementing the method as claimed in one of the preceding claims, comprising:

   - A first field device (11), which is configured to measure the first measured variable (L) with an adjustable measurement rate,

   - a second field device (12), which is configured to measure the second measured variable (f), wherein the first measured variable (L) is different from the second measured variable (f),

   - a control unit (4), which is configured

   ∘ to work out a correlation pattern between the first measured variable (L) and the second measured variable (f) based on the measured values from the calibration phase,

   ∘ to check at least the measured values of the second field device (12) in relation to the correlation pattern during measuring mode,

   ∘ to change at least the measurement rate of the first field device (11) in measuring mode at least during a time window (Δt, Δt₂) in which the correlation pattern is detected in the measured values of the second measured variable (f).
6. The measuring system as claimed in claim 5, wherein the first field device (11) and/or the second field device (12) comprise/comprises a battery to supply power.
7. The measuring system as claimed in claim 5 or 6, wherein the first field device (11) and/or the second field device (12) are/is connected to the control unit (14) by means of a wireless interface.

Images